If a scotter plot of y versus x has a positive coorelation, then?
If you are asking what it looks like, it should be lower on the left side and higher on the right side.
Pretend there is a general line following the direction that the dots are pointing. My teacher always told us that there is a little man that always starts walking on the very left of the graph. If he has to walk upward, it is a positive correlation, and if he has to walk downward, it is a negative correlation. I hope I helped a little!
Thanks,you did help, but the multiple choice answers are as y decreases, x increases etc. I know about the positive coorelation and stuff, i just need to know what happens WHEN you have a positive coorelation. Thanks for your help!
If a scatter plot of y versus x has a positive correlation, it means that as the values of x increase, the values of y also tend to increase. In other words, there is a systematic relationship between the two variables, where they both move in the same direction. To determine if a scatter plot exhibits a positive correlation, you can visually inspect the graph. However, if you want to analyze the relationship more precisely, you can calculate the correlation coefficient.
To calculate the correlation coefficient, you can use various statistical software or programming languages like Python, R, or Excel. Here's a step-by-step explanation of how to calculate the correlation coefficient using Python:
1. Gather your data: Collect the values of x and y for your scatter plot.
2. Import the required libraries: In Python, you need to import the NumPy library, which provides functions for mathematical calculations.
```python
import numpy as np
```
3. Create NumPy arrays for x and y data:
```python
x = np.array([x1, x2, x3, ...])
y = np.array([y1, y2, y3, ...])
```
Replace `x1, x2, x3, ...` with the actual values of x, and `y1, y2, y3, ...` with the actual values of y.
4. Use the `np.corrcoef()` function to calculate the correlation coefficient:
```python
correlation_matrix = np.corrcoef(x, y)
correlation_coefficient = correlation_matrix[0, 1]
```
The `corrcoef()` function returns a correlation matrix, and the correlation coefficient is the element in the top right corner (position `[0, 1]`).
5. Interpret the correlation coefficient:
- If the correlation coefficient is positive (between 0 and 1), it indicates a positive correlation.
- The closer the correlation coefficient is to 1, the stronger the positive correlation.
By following these steps, you will be able to analyze the scatter plot and determine if it exhibits a positive correlation.